Genetic markers of stomatal cluster development in Begoniaceae revealed through trait analysis assisted by interactive deep-learning.

Abstract

Stomata of plants track the immediate demand for carbon dioxide for photosynthesis while limiting transpirational water loss. Solitary stomatal patterns are common, yet some land plants develop noncontiguous stomatal clustering, where 2 or more stomata occur in groups and overlay a single air cavity. Clustering improves stomatal efficiency, reduces plant water use, and increases resilience to environment stress. How cluster development and physiology interact and integrate with the environment are open questions. Here we used TESSERA, a deep-learning platform for stomatal detection with an interactive interface for data review. Tracking Begonia stomatal clustering patterns across various Begonias, we have uncovered correlations for stomatal clustering traits. The stomatal parameter data were applied to identify genetic loci involved in Begonia stomatal development using quantitative trait locus analysis. Combined with differential gene expression to refine the candidate list, our analysis reveals known and potential new Begonia candidates in stomatal development. As a test of this knowledge, we cloned Begonia SPEECHLESS (BegSPCH), a loci identified in this screen and an established development-related gene in Arabidopsis. Unexpectedly, Arabidopsis spch-3 mutants transformed to express BegSPCH developed stomatal clusters unlike the mutant plants expressing AtSPCH. Thus, various molecular and environmental factors likely overlay transcriptional regulation in stomatal development.

Plant phenotyping relevance

TESSERAによる気孔検出プラットフォームを用いて気孔クラスタリング形質を抽出し、複数のBegoniaで解析しているため、植物表現型取得・解析手法が研究の中心的要素です。

Code and data availability

The paper's stomatal phenotype data are said to be in the article's Supplementary material (Tables S1–S4), but no public repository URL for these data is provided among the allowed URLs. The TESSERA deep-learning platform is available only by contacting the authors by email, with no public deposit URL. The 'vectors' at

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